Clinical Decision Support Systems (CDSSs) signify the framework shift in the medical sector in the modern age. CDSSs are utilized in augmenting healthcare facilities in the process of making complex clinical decisions. Since the first application of CDSSs in the 80s, the framework has witnessed significant transformation. The frameworks are now administered through electronic healthcare records with complex capacities. Irrespective of these complex advancements, there are existing questions concerning the impacts of CDSSs on service providers, healthcare costs, and patients’ records. There are many published texts concerning the success stories of CDSSs, but significant setbacks have proved that CDSSs are not without any potential risks. In this research, we provide critical analysis on the application of CDSSs in clinical setting, integrating various forms, present application cases with proven effectiveness, potential harms and common pitfalls. We therefore conclude with evidence-centered recommendation for mitigating the issues of CDSSs maintainability, evaluation, implementation and designing.
Diagnostic Decision Support System (DDSS), Clinical Decision Support Systems (CDSSs), Electronic Health Records (EHRs), Drug-Drug Integration (DDI).
R. B. Haynes, N. L. Wilczynski, and Computerized Clinical Decision Support System (CCDSS) Systematic Review Team, “Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: methods of a decision-maker-researcher partnership systematic review,” Implement. Sci., vol. 5, no. 1, p. 12, 2010.
M. Kinlay, W. Y. Zheng, R. Burke, I. Juraskova, R. Moles, and M. Baysari, “Medication errors related to computerized provider order entry systems in hospitals and how they change over time: A narrative review,” Res. Social Adm. Pharm., vol. 17, no. 9, pp. 1546–1552, 2021.
I. V. Angel and Department of Health Informatics and Analytics, Tufts University, School of Medicine, MA, USA, “A physician’s commentary on electronic health records in the United States medical practice,” Public Health (Fairfax), vol. 6, no. 1, pp. 9–11, 2021.
S. S. Gornale, S. Kumar, and P. S. Hiremath, “Handwritten signature Biometric data analysis for personality prediction system using machine learning techniques,” Trans. mach. learn. artif. intell., vol. 9, no. 5, pp. 1–22, 2021.
A. Bellesoeur et al., “Characterizing the risk of drug-drug interactions in sarcoma treated patients: Role of pharmacist integration,” Ann. Oncol., vol. 29 Suppl 8, no. suppl_8, pp. viii753–viii754, 2018.
K. Grunnet and J. E. Turrentine, “Patch testing in the diagnosis of medication allergy,” Curr. Treat. Options Allergy, vol. 3, no. 3, pp. 310–321, 2016.
S. Crepin et al., “Compliance of French academic clinical trials with the Clinical Trial Facilitation and Coordination Group recommendations on contraception and pregnancy testing requirements,” Clin. Trials, vol. 17, no. 3, pp. 314–322, 2020.
F. Philp, A. Faux-Nightingale, S. Woolley, E. de Quincey, and A. Pandyan, “Implications for the design of a Diagnostic Decision Support System (DDSS) to reduce time and cost to diagnosis in paediatric shoulder instability,” BMC Med. Inform. Decis. Mak., vol. 21, no. 1, p. 78, 2021.
S. Boch, E. Sezgin, D. Ruch, K. Kelleher, D. Chisolm, and S. Lin, “Unjust: the health records of youth with personal/family justice involvement in a large pediatric health system,” Health Justice, vol. 9, no. 1, p. 20, 2021.
National Nosocomial Infections Surveillance System, “National Nosocomial Infections Surveillance (NNIS) System Report, data summary from January 1992 through June 2004, issued October 2004,” Am. J. Infect. Control, vol. 32, no. 8, pp. 470–485, 2004.
Cite this article
Dowse R, “Advantages and Functions of Clinical and Decision Support Systems”, Journal of Biomedical and Sustainable Healthcare Applications, vol.2, no.1, pp. 043-050, January 2022. doi: 10.53759/0088/JBSHA202202006.